Abstract
Because there are a large number of data collection points and different standards in some large projects, there are many problems in data processing and maintenance. Therefore, the “intelligent integrated platform” came into being in this case and has become an effective means to solve the problem of information processing. This paper studies the intelligent integrated software development based on neural network fuzzy algorithm, introduces the neural network fuzzy algorithm into the intelligent integrated software development and application, and tests the developed software. The test results show that, according to the phenomenon that the smaller the variance is, the better the data fusion effect is, it is known that the software developed in this paper has a good effect in the data fusion, the minimum variance reaches 0.04, the maximum variance reaches 0.3, and the value of the variance is small in general. Then, in terms of the usage evaluation of the software, the overall usage evaluation of the software developed in this paper is good, about 75% of the software content is good, and about 69% of the software function is good, but the software has some shortcomings, mainly the human-machine interface design of the software is not very good.
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Wu, Y. (2022). Intelligent Integrated Software Development Based on Neural Network Fuzzy Algorithm. In: Macintyre, J., Zhao, J., Ma, X. (eds) The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy. SPIoT 2021. Lecture Notes on Data Engineering and Communications Technologies, vol 98 . Springer, Cham. https://doi.org/10.1007/978-3-030-89511-2_88
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DOI: https://doi.org/10.1007/978-3-030-89511-2_88
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